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Jurnal Doktor Manajemen 5 (2), September 2022
The Influence Of Transformational Leadership And Workload On The Performance Of BMKG Technicians During The Covid-19 Pandemic: Comparison Between Generations X, Y, And Z
Gregorius Setyadhi Budhi Dharmawan1); Mafizatun Nurhayati2); Hendri Satria WD3)
1) [email protected], Doctoral Program in Management Science, Faculty of Economics and Business, Mercubuana University, Indonesia
2) Doctoral Program in Management Science, Faculty of Economics and Business, Mercubuana University, Indonesia
3) Instrumenation Calibration and Engineering Center, BMKG Jakarta Corresponding Authors
I N F O ARTIKEL A B S T R A K
Kata kunci:
Covid-19, Transformational leadership, Workload, Performance, BMKG technician, Generation
Dikirim: 8 Feb 2022 Diterima: 11 Agustus 2022 Dipublikasikan:
9 September 2022
Alamat email penulis korespondensi:
gs.dharmawan@gm ail.com
The Covid-19 pandemic has an impact on all aspects of human life, not on public organizations. An organization requires management analysis related to efforts to achieve goals that depend on the individual performance of the organization in carrying out assigned tasks. The change in remote working patterns achieved by the pandemic has resulted in the transformation of leadership styles having to adapt to the current dynamics and work improvements felt by workers. This study aims to examine the effect of transformational leadership and workload during the Covid-19 pandemic on the performance of the Meteorology, Climatology and Geophysics Agency (BMKG) technicians with a focus on comparative analysis of generations X, Y, and Z. The population in this study were BMKG technicians who were scattered throughout Indonesia by calculating the sample using the Slovin formula. The method used in this study is quantitative with instrument testing to determine the validity and reliability of the data, then classical assumption test, accuracy model test and hypothesis. All test data processing uses the SPSS 25 application with a total sample of 232. The results of the study indicate that the data is normally distributed, valid and reliable with a significant Pearson correlation coefficient < 0.05 and Cronbach's Alpha (α) > 0.60.
Based on classical assumptions, model accuracy variables, and the hypothesis obtained is that transformational leadership and workload variables have a positive effect on performance. The intergenerational comparison analysis for the transformational leadership variable has the greatest positive effect on Generation Z, and workload has the largest positive effect on Generation X on technicians during the pandemic.
103 1. PENDAHULUAN
The phenomenon of Covid-19 is a global pandemic that is very disturbing and disrupts all segments of human life on earth (Yulianti et al, 2021). Many countries have decided to close all forms of social activities such as education and work that are changed by online methods. During the Covid-19 pandemic, human resources are the most important thing for public organizations, which essentially function as a driving factor for every activity within the organization.
The success of an organization cannot be separated from the participation of employees and all levels in it. Employees are the spearhead that determines the success or failure of the implementation of activities in the organization. If all employees and other staff are able to work well and maximally, the organizational goals will be achieved (Utomo and Supriyanto, 2020). The Covid-19 pandemic has resulted in rapid changes in the work operations of the technicians of the Meteorology, Climatology and Geophysics Agency. The Meteorology, Climatology and Geophysics Agency (BMKG) is an institution / organization that carries out government duties in the fields of Meteorology, Climatology, Air Quality and Geophysics in accordance with the provisions of the applicable legislation. Based on clause 48 subsection 1 of Law Number 31 of 2009 it is stated that every observation equipment operated at the observation station must be operationally feasible and in subsection 4 it is stated that any observation equipment that is not operationally feasible is prohibited from being operated, so that reliable technicians are needed to maintain BMKG equipment. well awake. BMKG has 550 technicians spread throughout Indonesia who are tasked with maintaining and repairing BMKG operational equipment so that organizational performance can run as well as possible.
When observed from the age level of BMKG technicians, there is a diversity of generations working.
Generational differences can also indicate differences in the characteristics of the workforce in dealing with dynamics in an organization that can have an impact on their performance. This is inseparable from the diversity of the nature of employees from various generations who work in an organization. If 15-20 years ago an organization could only fill 1 generation, now it is different because it can reach 3 generations at once, namely generations X, Y, and Z. Differences in personality and ways of working can be an obstacle to the progress of an organization. DelCampo et al (2017) stated that it is important to understand generation because it can help organizations map out the steps involved in recruitment, training, and protection. There are still not many previous studies that have carried out performance studies related to generational differences, let alone related to the Covid-19 pandemic. Schawbel (2020) found that before the pandemic the younger generation was most interested in work flexibility, while the older generation was more likely to have flexibility. However, during this pandemic, young people have a more pessimistic view of remote work than they have as research by Shibata (2021) says job digitization (WFH) will lead to closer supervision and job performance. While younger generations are more likely to want remote work and more likely to adopt and use collaborative tools, the vast majority of Generation Z (95%) and Millennials (93%) have difficulty working remotely during the pandemic.
Compared to Generation X, this younger generation reports that they feel less connected, are less informed about what's going on at their company, say that video calls have hurt their productivity, and have difficulty working with their coworkers remotely.
As a leader in a time of pandemic, you also face situations that are largely unheard of before, and for which there are no clear answers. Policies made in the dynamics that occur in the external and internal environment of the organization may have an impact on the performance of their subordinates. The pandemic also has an impact on an increasing workload, or the same workload but with greater constraints in the field, which can also have an impact on employee performance (Murphy, 2020). With the pandemic conditions, leaders at BMKG must have a good strategy to overcome existing patterns of change to determine the workload so that they can optimize the performance of employees, especially technicians. There are three indicators used to measure workload (Koesomowidjojo, 2017), including; 1) working conditions; 2) use of working time; and 3) targets to be achieved. Of course, in the conditions of the Covid-19 pandemic, all of these variables must be adjusted considering the target of BMKG equipment which must remain feasible through policies made by transformational leaders.
Covid-19 has greatly impacted all parties, changes in work methods and patterns that must comply with health protocols affect the workload (Cahyo et al, 2021) and of course changes in the workload of BMKG technicians which increase. This causes changes in the work system due to the PSBB pattern to PPKM with demands for equipment that must always be feasible and makes the workload given bigger than before. This condition becomes a challenge for leaders to evaluate the management of their human resources, so that the performance of technicians remains in a stable condition. This study aims to analyze the effect of transformational leadership and workload on the performance of BMKG technicians during the Covid-19 pandemic by comparing the performance of Generations X, Y, and Z. Is there a difference in the effect of transformational leadership and workload on the performance of technicians during the pandemic in Generation X? compared to the performance of technicians in Generation Y, and in Generation Z who have started to enter the workforce. This research is interesting to do because analyzing employee performance by comparing different generations with different characteristics of each is still rarely done, especially in public organizations. From the results of this study, it is hoped that it can provide information and input for organizations, especially public organizations in managing generational differences within their organizations.
104 LITERATURE REVIEW
Generation Difference Theory
Generation X is the generation born in 1965-1980, the early years of the development of technology and information, such as the use of computers (personal computers), video games, cable television and the internet. The characteristics of this generation are: the ability to adapt, the ability to accept change well and is referred to as a difficult generation, has an independent and loyal personality, prioritizes image, fame and money, the type of hard work, and responsibility. the company's contribution to the work (Jurkiewicz, 2000). Generation Y born in 1981-1995 is known as the Millennial generation. This generation uses a lot of instant communication technologies such as email, SMS, instant messaging, and social networks such as Facebook and Twitter, in other words Generation Y is a generation that grew up in the internet boom era (Lyon et al, 2005). The characteristics of this generation are: adaptability, ability to accept change well and are referred to as a difficult generation, have an independent and loyal personality, prioritize image, fame and money, work hard, and calculate contributions. made by the company on the work (Jurkiewicz, 2000).
Research by Bencsik, Csikos, and Juhez (2016) shows that the younger generation who have just entered the workforce is Generation Z (born 1996-present), which is also known as iGeneration or the Internet generation.
Generation Z is similar to Generation Y, but Generation Z is able to perform all activities simultaneously (multitasking) such as: running social networks using mobile phones, browsing with computers, and listening to music using headsets.
Everything that is done is mainly related to the virtual world. Since childhood, this generation is familiar with technology and is familiar with sophisticated devices that indirectly affect personality.
Social Change: A Concept in the COVID-19 Pandemic Phenomenon
Social change is a dynamic of life that must be experienced by humans during their lives. According to Samuel Koening, social change is a change or modification that occurs in a person's lifestyle. The reason for the modification can be from the internal environment of the community and can also come from outside the community (Ichsan, 2020).
Social changes also arise as a result of global disasters that "force" the world's citizens to deal with them in unusual ways. As for the people affected by the latter case, they will experience social changes in almost all aspects of their lives.
With it they will experience fundamental and comprehensive changes, namely changes in the social system of society (the change of the social system). If it is a catastrophe of the Covid-19 pandemic, the purpose of changing the social system is for society to experience three changes, including: 1). Changes in physical culture, such as every time you leave the house you have to wear a mask, wash your hands when you get home, etc. 2). Changes in regulations, such as how to live together while maintaining physical distance from each other, not meeting in large numbers, etc. 3). Changes in the value system, such as people who maintain cleanliness, care more about the environment, etc. (Ichsan, 2020).
Employee Performance and Transformational Leadership
Employee performance is the result of the work of the organization, which is carried out by employees as well as possible with the instructions and directions given by the leadership, competence and ability of employees in developing reason at work (Abdullah, 2014). Transformational leadership is defined as leadership that includes organizational change efforts that can lead to superior performance in organizations that are facing demands for renewal and change. The success or failure of employees in work performance can also be influenced by the leadership of their superiors (Giovanni, 2014) so that it will produce performance with competency-based quality that a person has in an organization. Characteristics between different generations can also have an impact on the different effects of transformational leadership on employee performance (DelCampo et al, 2017). Siswanto and Hamid's research (2017) with quantitative methods found that leadership style has a positive and significant effect on employee performance, and transformational leadership variables and organizational culture have a significant effect on employee innovative behavior (Parashakti et al, 2016).
H1: There is a difference in the effect of transformational leadership on employee performance between Generations X, Y, and Z during the Covid-19 Pandemic.
Employee Performance and Workload
Workload can be identified as a difference between the capacity or ability of workers and the demands of the work that must be faced (Astianto, 2014). Schawbel (2020) found that during this pandemic, young people have a more pessimistic view of remote work. While younger generations are more likely to want remote work and more likely to adopt and use collaborative tools, most Generation Z and Millennials are having a hard time working remotely during the pandemic. The increased workload coupled with the obstacles faced magnify the impact experienced in its performance. Rindyandana and Astuti (2017) in their research state that workload has a positive effect on employee performance, this is in line with research by Setiawan (2020). The study analyzed the effect of changing work shifts during the Covid-19 pandemic on performance, where work time was included in the workload indicator.
H2: There is a difference in the effect of workload on employee performance between Generations X, Y, and Z during
105 the Covid-19 Pandemic.
2. METHODS
The type of research used is quantitative with a survey method through a correlational research approach. The instrument used to measure transformational leadership is an adaptation of Podsakoff et al (1990) with indicators:
Idealized Influence (charisma), Inspirational Motivation (inspiration), Intellectual Stimulation (intellectual stimulation), and Individualized Consideration (individual considerations). Workload for 18 months during the pandemic through an approach by Putra with indicators: targets to be achieved, working conditions, use of time, and work standards.
Performance technicians use the same measurements as indicators: quality, quantity, timeliness, and work commitment.
The variable measurement scale uses a Likert scale for opinions from strongly disagree to strongly agree with a weight of 1-5. The technique of collecting research data is through the distribution of research instruments in the form of a questionnaire using Google Form. The data analysis technique uses multiple linear regression analysis with three models, namely multiple linear regression analysis for the performance model of technicians of generation X, generation Y, and generation Z.
The population of this study was 550 BMKG technicians throughout Indonesia, but due to the large number of populations, the Slovin formula was used to obtain the number of samples needed to represent the entire population. In the calculation of the population of this study, a margin of error of 5% was set so that n was obtained as many as 232 minimum samples from the questionnaire results to represent the entire population of BMKG technicians.
3. RESULT AND DISCUSSION Respondent Profile
The number of samples obtained in this study were 239 BMKG technicians with respondent profiles including gender; generation which is divided into generation X (41 – 58 years), generation Y (26-40 years), generation Z (21-25 years); years of service; and the last education of the BMKG Technician according to the discrete data (Rachbini et al, 2018) obtained.
Figure 1. Respondent Profile
Based on Figure 1 above, it can be seen that the respondents are dominated by male sex as much as 75%. The working period of most respondents is > 10 years by 42%. From the profile of the generation of respondents, it is dominated by generation Y or millennial generation (26-40 years) by 48%. And the last education of respondents was dominated by Bachelor degree of Instrumentation by 71%.
Instrument Test Results Validity and Reliability Test
Table 1. Validity and Reliability Test Result Variable Question
Items
Pearso n Cor.
Sig.
Level Description Cronbach’
s Alpha (α) Description Transformative
Leadership
KT_1 0.806 0.000 Valid
0.899 Reliable KT_2 0.804 0.000 Valid
KT_3 0.837 0.000 Valid
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KT_4 0.892 0.000 Valid KT_5 0.743 0.000 Valid KT_6 0.814 0.000 Valid
Workload
BK_1 0.698 0.000 Valid
0.684 Reliable BK_2 0.744 0.000 Valid
BK_3 0.643 0.000 Valid BK_4 0.698 0.000 Valid BK_5 0.746 0.000 Valid BK_6 0.314 0.000 Valid
Performance
KT_1 0.711 0.000 Valid
0.786 Reliable KT_2 0.743 0.000 Valid
KT_3 0.752 0.000 Valid KT_4 0.676 0.000 Valid KT_5 0.693 0.000 Valid KT_6 0.631 0.000 Valid
Based on Table 1 shows that all the questions on the variables of Transformational Leadership, Workload, and Performance are declared valid, with a positive and significant Pearson correlation coefficient <0.05. This means that all questions on these variables can be accepted for processing.
In reliability testing, it can be seen that each variable gives Cronbach's Alpha (α) value > 0.60. So that all the variables used in this study are declared reliable, meaning that the stability and consistency of the measuring instruments used are consistent.
Classic Assumption Test Results
This study used the Kolmogorov – Smirnov normality test. The test results using the Kolmogorov Smirnoff method from the calculation results obtained that the Asymp sig Unstandardized Residual Regression value was 0.097
> 0.05 so it could be concluded that all data in this study were normally distributed. The results of the multicollinearity test can be seen if the overall tolerance value is > 0.1 and the overall VIF value is < 10, so it can be concluded that there is no multicollinearity between the independent variables. Thus the assumption test of the absence of multicollinearity can be fulfilled. The results of the heteroscedasticity test also show that there is no heteroscedasticity, that the remainder has a homogeneous (constant) variance or in other words there are no symptoms of heteroscedasticity.
Results of Model Accuracy Test and Hypothesis Test
Based on the calculation results, the results are shown in Table 2. In the coefficient of determination test results, it is found that the Generation X performance model is the best model compared to the Generation Y and Generation Z performance models, indicated by the Adjusted R Square of 0.623 which indicates the contribution of transformational leadership. and the workload in explaining the performance of BMKG technicians during the Covid-19 pandemic was 62.3%, greater than 50%, while in Generation Y it was 38.1%, and in Generation Z it was 41.6%.
When analyzed using ANOVA, the performance model of Generation X is the best model compared to the performance model of Generation Y and Generation Z, indicated by the F statistic value of 53,117 compared to the F statistic of the performance model of Generation Y and Generation Z of 36,146 and 21,987. However, the three models are declared correct because the significance value is smaller than alpha 0.05.
Table 2. Results of Model Accuracy Test and Hypothesis Test
Hypothesis
GenX Performance Model GenY Performance Model GenZ Performance Model
Conclucio Coefficient n
regression t-statistic Sig Coefficient
regression t-statistic Sig Coefficient
regression t-statistic Sig constant 9.053 5.715 0.00 11.985 8.280 0.000 9.246 3.985 0.000
H1: KT � K 0.163 2.054 0.044 0.190 3.061 0.003 0.263 2.928 0.005 H1 accepted H2: BK � K 0.510 5.557 0.000 0.349 4.664 0.000 0.391 3.313 0.002 H1 accepted
Adjusted R2 0.623 0.381 0.416
F statistic 53.117 36.146 21.987
Sig F 0.000 0.000 0.000
Source: Results of data processing using SPSS 25, 2021.
From Table 2, it can be shown that transformational leadership has a positive and significant effect on the performance of BMKG technicians during the Covid 19 pandemic both in Generation X, Generation Y, and Generation Z. Transformational leadership has the lowest effect, followed by Generation Y, and the strongest influence on
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transformational leadership on technician performance is Generation Z. Based on the significance test, it looks smaller than alpha 0.05, so it is stated that transformational leadership has a positive and significant effect on the performance of BMKG technicians in the three generations.
The effect of workload on employee performance shows that in the three generations each has a positive and significant effect, seen from the significance value, each of which has a significance value smaller than alpha 0.05. The biggest influence on Generation X, followed by Generation Z, and finally on Generation Y, is clearly seen in the regression coefficient value of the test results, which is largest at 5.10, followed by Generation Z at 0.391, and finally in Generation Y at 0.349.
DISCUSSION
From the results of hypothesis testing, it is proven that transformational leadership has a positive and significant effect on the performance of BMKG technicians during the Covid 19 pandemic both in Generation X, Generation Y, and Generation Z. The results of this analysis are in line with research by Wahyuningsih and Sudibjo (2021) which shows that there is an influence of positive and significant transformational leadership style and work environment on job satisfaction of millennial generation employees. When job satisfaction is achieved by employees, it can certainly improve performance. Research by Putra and Johanes (2017) shows the most dominant influence of leadership and of course has an impact on employee performance in carrying out tasks. If observed more deeply, it can be seen that in Generation X the influence of transformational leadership has the lowest effect, followed by Generation Y, and the strongest influence on transformational leadership on technician performance is in Generation Z. The results of this study support the statement of Madden (2017) in his book Hello Gen Z, that Generation Z desperately needs leaders with a transformational leadership style who can connect and inspire them for a big cause. It can be explained that based on the phenomena that occurred at BMKG, the role of leadership has a direct impact on generation Z who are millennial generation technicians (baby boomers) and are affected by transformational leadership patterns while working during the pandemic through motivation, managerial considerations, and trust. This millennial generation of BMKG technicians carries out the biggest task when social restriction due to COVID-19 conditions with the obligation to continue working in the office even though other employees work with the Work From Home (WFH) system, so that leaders who always support technicians personally and know what technicians need have a positive effect greatest on performance.
The effect of workload on employee performance shows that each of the three generations has a positive and significant effect. This is in line with the research results of Wahdaniah and Gunardi (2018) which show a significant effect of workload on performance. Irawati and Carollina, (2017) in their research also show that workload internally has a positive effect on employee performance. The biggest influence is on Generation X, followed by Generation Z, and finally on Generation Y. Based on the policies that occurred during the pandemic where the average Generation X technician has worked for decades and when work is given with a certain workload, performance will only increase.
However, it is different for Generation Z who just joined as BMKG technicians during the pandemic, so the transfer time of knowledge from Generation X and Y is still minimal. It is observed that the workload given to generation Z is also in accordance with the ability and has a moderate effect (between generations X and Y) on performance. Generation Y has the lowest influence on performance where even this generation before the pandemic conditions was used to excessive workloads and demands for extra work and being active in maintaining BMKG operational equipment. In contrast to Generation X, which has the greatest impact on performance during the pandemic, due to more experience.
So that a positive increase in workload has the lowest coefficient of performance improvement in Generation Y.
CONCLUSIONS AND SUGGESTIONS Conclusions
Based on the research that has been done, the following conclusions can be obtained:
1) Transformational leadership has a positive and significant effect on the performance of BMKG technicians during the Covid-19 pandemic both in Generation X, Generation Y, and Generation Z. In Generation X the influence of transformational leadership is the lowest, followed by Generation Y, and the strongest is the influence of transformational leadership on technicians' performance in Generation Z. Leaders are expected to maintain a climate of transformational leadership, by showing behaviors that make employees believe that they consistently become a source of inspiration and motivation, perform intellectual stimulation, and provide individual attention (Winasis et al, 2021) so that they will indirectly improve employee performance.
2) The workload experienced has a positive and significant impact on the performance of BMKG Technicians during the Covid-19 pandemic with the highest impact on Generation X. This means that when the perceived workload is in accordance with abilities, the performance of BMKG technicians will also increase.
Suggestions
Based on the research results, it is necessary to conduct intensive knowledge transfer for both Generation X, Generation Y, and Generation Z technicians at BMKG so that the workload can be adjusted for more optimal
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performance. For workload analysis, it can analyze how job satisfaction from employees which continues with a positive influence will have an impact on employee performance (Lubis and Nurhayati, 2020). With some limitations in this study, the addition of other variables can be done to analyze how they affect performance so that it can be seen which variables are more and most influential with better test results such as competence, compensation, and work environment. As well as an analysis of how the role of the proposed variables can improve more optimal results through the application of mediating and moderating variables.
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